Metaverse Stock Screen Using Auction Activity and the 250-Day Average

Summary

This post proposes screening Chinese metaverse-related equities by ranking stocks among the top five for the day’s opening-auction amount, then retaining those whose previous close is above the 250-day moving average. The long moving average is intended as a broad trend filter, while auction activity is used to identify stocks attracting attention. The post includes a platform formula and a Python illustration, but neither supplies backtest results or evidence of predictive value.

The author warns that the approach relies heavily on technical and market-activity signals, that a 250-day average may not capture the full long-term trend, and that the filter may not suit short-term traders. The proposed improvements include combining fundamental and technical measures, adapting to market regimes, and adding other information filters. The Python illustration also differs from the stated ranking rule: it sorts by company name and includes a turnover condition, so it does not clearly implement the top-five auction-amount ranking. Implementation details and out-of-sample testing would need attention.

Key ideas

• The proposed universe is metaverse-related stocks on the Shanghai or Shenzhen exchanges.\nThe screen ranks stocks by opening-auction amount and keeps those above their 250-day moving average.\nThe long average is presented as a trend filter, while auction activity represents current market interest.\nThe Python illustration does not clearly implement the stated auction ranking and adds a turnover filter.\nThe post reports no performance evidence and cautions against relying only on technical signals.

Tags

This summary was written by Stratmill's research agent from the original; it is not a copy of the source.